Merge branch 'bsm2' of https://github.com/QSD-Group/EXPOsan

exposan/bsm1/README.rst

@@ -4,7 +4,7 @@ bsm1: Benchmark Simulation Model No. 1
 
 Summary
 -------
-This module implements the Benchmark Simulation Model No. 1 (BSM1). [1]_ The code for process modeling and dynamic simulation has been verified against the MATLAB/Simulink [2]_ implementation developed by International Water Association (IWA) Task Group on Benchmarking of Control Strategies. The ``data`` folder contains the outputs from MATLAB/Simulink results (``matlab_exported_data.xlsx`` and ``matlab_workspace.mat``) for comparison.
+This module implements the Benchmark Simulation Model No. 1 (BSM1). [1]_ The code for process modeling and dynamic simulation has been verified against the MATLAB/Simulink [2]_ implementation developed by International Water Association (IWA) Task Group on Benchmarking of Control Strategies. The ``data`` folder contains the outputs from MATLAB/Simulink results (``matlab_exported_data_asm1.xlsx`` and ``matlab_workspace_asm1.mat``) for comparison.
 
 .. figure:: ./readme_figures/bsm1.png
 

exposan/bsm1/model.py

@@ -19,13 +19,15 @@
 from exposan.bsm1 import (
     biomass_IDs,
     create_system,
-    default_init_conds as _ic,
+    default_init_conds,
     results_path,
     Q, Q_was, V_an, V_ae,
     )
 
 __all__ = ('create_model', 'run_uncertainty', 'run_wdiff_init',)
 
+_ic = default_init_conds['asm1']
+
 
 #%%
 

exposan/bsm1/system.py

@@ -21,7 +21,9 @@
 __all__ = (
     'biomass_IDs',
     'create_system',
-    'default_asm_kwargs', 'default_inf_kwargs', 'default_init_conds',
+    'default_asm_kwargs',
+    'default_inf_kwargs',
+    'default_init_conds',
     'Q', 'Q_ras', 'Q_was', 'Temp', 'V_an', 'V_ae', 
     )
 
@@ -47,7 +49,9 @@
 # aer.B = 1750.286
 # aer.C = 235.0
 
-default_inf_kwargs = {
+valid_models = ('asm1', 'asm2d')
+default_inf_kwargs = dict.fromkeys(valid_models)
+default_inf_kwargs['asm1'] = {
     'concentrations': {
         'S_S':69.5,
         'X_BH':28.17,
@@ -62,31 +66,86 @@
     'units': ('m3/d', 'mg/L'),
     }
 
-default_asm_kwargs = dict(
+default_inf_kwargs ['asm2d'] = {
+    'concentrations': {
+      'S_I': 14,
+      'X_I': 26.5,
+      'S_F': 20.1,
+      'S_A': 94.3,
+      'X_S': 409.75,
+      'S_NH4': 31,
+      'S_N2': 0,
+      'S_NO3': 0.266, 
+      'S_PO4': 2.8,
+      'X_PP': 0.05,
+      'X_PHA': 0.5,
+      'X_H': 0.15,
+      'X_AUT': 0, 
+      'X_PAO': 0, 
+      'S_ALK':7*12,
+      },
+    'units': ('m3/d', 'mg/L'),
+    }
+
+default_asm_kwargs = dict.fromkeys(valid_models)
+default_asm_kwargs['asm1'] = dict(
     Y_A=0.24, Y_H=0.67, f_P=0.08, i_XB=0.08, i_XP=0.06,
     mu_H=4.0, K_S=10.0, K_O_H=0.2, K_NO=0.5, b_H=0.3,
     eta_g=0.8, eta_h=0.8, k_h=3.0, K_X=0.1, mu_A=0.5,
     K_NH=1.0, b_A=0.05, K_O_A=0.4, k_a=0.05, fr_SS_COD=0.75,
     path=os.path.join(data_path, '_asm1.tsv'),
     )
 
-default_init_conds = {
-        'S_S':5,
-        'X_I':1000,
-        'X_S':100,
-        'X_BH':500,
-        'X_BA':100,
-        'X_P':100,
-        'S_O':2,
-        'S_NO':20,
-        'S_NH':2,
-        'S_ND':1,
-        'X_ND':1,
-        'S_ALK':7*12,
+default_asm_kwargs['asm2d'] = dict(
+    iN_SI=0.01, iN_SF=0.03, iN_XI=0.02, iN_XS=0.04, iN_BM=0.07,
+    iP_SI=0.0, iP_SF=0.01, iP_XI=0.01, iP_XS=0.01, iP_BM=0.02,
+    iTSS_XI=0.75, iTSS_XS=0.75, iTSS_BM=0.9,
+    f_SI=0.0, Y_H=0.625, f_XI_H=0.1,
+    Y_PAO=0.625, Y_PO4=0.4, Y_PHA=0.2, f_XI_PAO=0.1,
+    Y_A=0.24, f_XI_AUT=0.1,
+    K_h=3.0, eta_NO3=0.6, eta_fe=0.4, K_O2=0.2, K_NO3=0.5, K_X=0.1,
+    mu_H=6.0, q_fe=3.0, eta_NO3_H=0.8, b_H=0.4, K_O2_H=0.2, K_F=4.0,
+    K_fe=4.0, K_A_H=4.0, K_NO3_H=0.5, K_NH4_H=0.05, K_P_H=0.01, K_ALK_H=0.1,
+    q_PHA=3.0, q_PP=1.5, mu_PAO=1.0, eta_NO3_PAO=0.6, b_PAO=0.2, b_PP=0.2,
+    b_PHA=0.2, K_O2_PAO=0.2, K_NO3_PAO=0.5, K_A_PAO=4.0, K_NH4_PAO=0.05,
+    K_PS=0.2, K_P_PAO=0.01, K_ALK_PAO=0.1,
+    K_PP=0.01, K_MAX=0.34, K_IPP=0.02, K_PHA=0.01,
+    mu_AUT=1.0, b_AUT=0.15, K_O2_AUT=0.5, K_NH4_AUT=1.0, K_ALK_AUT=0.5, K_P_AUT=0.01,
+    k_PRE=1.0, k_RED=0.6, K_ALK_PRE=0.5,
+    )
+
+default_init_conds = dict.fromkeys(valid_models)
+default_init_conds['asm1'] = {
+    'S_S':5,
+    'X_I':1000,
+    'X_S':100,
+    'X_BH':500,
+    'X_BA':100,
+    'X_P':100,
+    'S_O':2,
+    'S_NO':20,
+    'S_NH':2,
+    'S_ND':1,
+    'X_ND':1,
+    'S_ALK':7*12,
+    }
+
+default_init_conds['asm2d'] = {
+    'S_F':5,
+    'S_A':2,
+    'X_I':1000,
+    'X_S':100,
+    'X_H':500,
+    'X_AUT':100,
+    #'X_P':100,
+    'S_O2':2,
+    'S_NO3':20,
+    'S_NH4':2,
+    'S_ALK':7*12,
     }
 
-def batch_init(sys, path, sheet):
-    df = load_data(path, sheet)
+
+def batch_init(sys, df):
     dct = df.to_dict('index')
     u = sys.flowsheet.unit # unit registry
     for k in [u.A1, u.A2, u.O1, u.O2, u.O3]:
@@ -105,16 +164,52 @@ def batch_init(sys, path, sheet):
 # Benchmark Simulation Model No. 1
 # =============================================================================
 
-def create_system(flowsheet=None, inf_kwargs={}, asm_kwargs={}, init_conds={},
-                  aeration_processes=()):
+def create_system(
+        flowsheet=None, 
+        suspended_growth_model='ASM1',
+        inf_kwargs={},
+        asm_kwargs={},
+        init_conds=None,
+        aeration_processes=(),
+        ):
+    '''
+    Create the system as described in Benchmark Simulation Model No.1.
+    
+    Parameters
+    ----------
+    flowsheet : obj
+        Flowsheet where this system will be created on.
+    suspended_growth_model : str
+        Either "ASM1" using Activated Sludge Model No. 1,
+        or "ASM2d" using Activated Sludge Model No. 2d.
+    inf_kwargs : dict
+        Keyword arguments for influent.
+    asm_kwargs : dict
+        Keyword arguments for the ASM model (ASM1 or ASM2d).
+    init_conds : dict or DataFrame
+        For a dict, keyword arguments for initial conditions for all bioreactors in the system
+        (the same initial conditions will be used),
+        or a pandas.DataFrame that contains initial conditions for each unit.
+        Default initial conditions will be used if not given.
+    '''
     flowsheet = flowsheet or qs.Flowsheet('bsm1')
     qs.main_flowsheet.set_flowsheet(flowsheet)
 
     # Components and stream
-    pc.create_asm1_cmps()
+    kind = suspended_growth_model.lower().replace('-', '').replace('_', '')
+    if kind == 'asm1':
+        pc.create_asm1_cmps()
+        asm = pc.ASM1(**default_asm_kwargs[kind])
+        DO_ID = 'S_O'
+    elif kind == 'asm2d':
+        pc.create_asm2d_cmps()
+        asm = pc.ASM2d(**default_asm_kwargs[kind])
+        DO_ID = 'S_O2'
+    else: raise ValueError('`suspended_growth_model` can only be "ASM1" or "ASM2d", '
+                           f'not {suspended_growth_model}.')
 
     wastewater = WasteStream('wastewater', T=Temp)
-    inf_kwargs = inf_kwargs or default_inf_kwargs
+    inf_kwargs = inf_kwargs or default_inf_kwargs[kind]
     wastewater.set_flow_by_concentration(Q, **inf_kwargs)
 
     effluent = WasteStream('effluent', T=Temp)
@@ -126,27 +221,25 @@ def create_system(flowsheet=None, inf_kwargs={}, asm_kwargs={}, init_conds={},
     if aeration_processes:
         aer1, aer2, aer3 = aeration_processes
     else:
-        aer1 = aer2 = pc.DiffusedAeration('aer1', 'S_O', KLa=240, DOsat=8.0, V=V_ae)
-        aer3 = pc.DiffusedAeration('aer3', 'S_O', KLa=84, DOsat=8.0, V=V_ae)
-    asm_kwargs = asm_kwargs or default_asm_kwargs
-    asm1 = pc.ASM1(**asm_kwargs)
+        aer1 = aer2 = pc.DiffusedAeration('aer1', DO_ID, KLa=240, DOsat=8.0, V=V_ae)
+        aer3 = pc.DiffusedAeration('aer3', DO_ID, KLa=84, DOsat=8.0, V=V_ae)
 
     # Create unit operations
     A1 = su.CSTR('A1', ins=[wastewater, RWW, RAS], V_max=V_an,
-                  aeration=None, suspended_growth_model=asm1)
+                 aeration=None, suspended_growth_model=asm)
 
     A2 = su.CSTR('A2', A1-0, V_max=V_an,
-                  aeration=None, suspended_growth_model=asm1)
+                 aeration=None, suspended_growth_model=asm)
 
     O1 = su.CSTR('O1', A2-0, V_max=V_ae, aeration=aer1,
-                  DO_ID='S_O', suspended_growth_model=asm1)
+                 DO_ID=DO_ID, suspended_growth_model=asm)
 
     O2 = su.CSTR('O2', O1-0, V_max=V_ae, aeration=aer2,
-                  DO_ID='S_O', suspended_growth_model=asm1)
+                 DO_ID=DO_ID, suspended_growth_model=asm)
 
     O3 = su.CSTR('O3', O2-0, [RWW, 'treated'], split=[0.6, 0.4],
                  V_max=V_ae, aeration=aer3,
-                  DO_ID='S_O', suspended_growth_model=asm1)
+                 DO_ID=DO_ID, suspended_growth_model=asm)
 
     C1 = su.FlatBottomCircularClarifier('C1', O3-1, [effluent, RAS, WAS],
                                         underflow=Q_ras, wastage=Q_was, surface_area=1500,
@@ -170,8 +263,14 @@ def create_system(flowsheet=None, inf_kwargs={}, asm_kwargs={}, init_conds={},
     # sys = System('bsm1_sys', path=(bio, C1, S1), recycle=(RAS,))
 
     if init_conds:
-        for i in [A1, A2, O1, O2, O3]: i.set_init_conc(**init_conds)
-    else: batch_init(sys, os.path.join(data_path, 'initial_conditions.xlsx'), 'default')
+        if type(init_conds) is dict:
+            for i in [A1, A2, O1, O2, O3]: i.set_init_conc(**init_conds)
+        else:
+            df = init_conds
+    else: 
+        path = os.path.join(data_path, f'initial_conditions_{kind}.xlsx')
+        df = load_data(path, sheet='default')
+        batch_init(sys, df)
     sys.set_dynamic_tracker(A1, effluent)
     sys.set_tolerance(rmol=1e-6)
 

exposan/bsm2/__init__.py

@@ -18,7 +18,8 @@
 
 bsm2_path = os.path.dirname(__file__)
 module = os.path.split(bsm2_path)[-1]
-data_path, results_path = _init_modules(module, include_data_path=True)
+data_path, results_path, figures_path = \
+    _init_modules(module, include_data_path=True, include_figures_path=True)
 
 
 # %%
@@ -52,6 +53,7 @@ def __getattr__(name):
 
 __all__ = (
     'bsm2_path',
+    'figures_path',
     'results_path',
     *system.__all__,
 )